Tilting at quixotic trait loci (QTL): an evolutionary perspective on genetic causation

Spontaneous single-nucleotide substitutions and microsatellite mutations have distinct distributions of fitness effects

The fitness effects of new mutations determine key properties of evolutionary processes. Beneficial mutations drive evolution, yet selection is also shaped by the frequency of small-effect deleterious mutations, whose combined effect can burden otherwise adaptive lineages and alter evolutionary trajectories and outcomes in clonally evolving organisms such as viruses, microbes, and tumors. The small effect sizes of these important mutations have made accurate measurements of their rates difficult. In microbes, assessing the effect of mutations on growth can be especially instructive, as this complex phenotype is closely linked to fitness in clonally evolving organisms. Here, we perform high-throughput time-lapse microscopy on cells from mutation-accumulation strains to precisely infer the distribution of mutational effects on growth rate in the budding yeast, Saccharomyces cerevisiae. We show that mutational effects on growth rate are overwhelmingly negative, highly skewed towards very small effect sizes, and frequent enough to suggest that deleterious hitchhikers may impose a significant burden on evolving lineages. By using lines that accumulated mutations in either wild-type or slippage repair-defective backgrounds, we further disentangle the effects of 2 common types of mutations, single-nucleotide substitutions and simple sequence repeat indels, and show that they have distinct effects on yeast growth rate. Although the average effect of a simple sequence repeat mutation is very small (approximately 0.3%), many do alter growth rate, implying that this class of frequent mutations has an important evolutionary impact.

Spontaneous single-nucleotide substitutions and microsatellite mutations have distinct distributions of fitness effects

The fitness effects of new mutations determine key properties of evolutionary processes. Beneficial mutations drive evolution, yet selection is also shaped by the frequency of small-effect deleterious mutations, whose combined effect can burden otherwise adaptive lineages and alter evolutionary trajectories and outcomes in clonally evolving organisms such as viruses, microbes, and tumors. The small effect sizes of these important mutations have made accurate measurements of their rates difficult. In microbes, assessing the effect of mutations on growth can be especially instructive, as this complex phenotype is closely linked to fitness in clonally evolving organisms. Here, we perform high-throughput time-lapse microscopy on cells from mutation-accumulation strains to precisely infer the distribution of mutational effects on growth rate in the budding yeast, Saccharomyces cerevisiae. We show that mutational effects on growth rate are overwhelmingly negative, highly skewed towards very small effect sizes, and frequent enough to suggest that deleterious hitchhikers may impose a significant burden on evolving lineages. By using lines that accumulated mutations in either wild-type or slippage repair-defective backgrounds, we further disentangle the effects of two common types of mutations, single-nucleotide substitutions and simple sequence repeat indels, and show that they have distinct effects on yeast growth rate. Although the average effect of a simple sequence repeat mutation is very small (~0.3%), many do alter growth rate, implying that this class of frequent mutations has an important evolutionary impact.

Disparate genetic variants associated with distinct components of cowpea resistance to the seed beetle Callosobruchus maculatus

Polygenic genome-wide association mapping identified two regions of the cowpea genome associated with different components of resistance to its major post-harvest pest, the seed beetle Callosobruchus maculatus. Cowpea (Vigna unguiculata) is an important grain and fodder crop in arid and semi-arid regions of Africa, Asia, and South America, where the cowpea seed beetle, Callosobruchus maculatus, is a serious post-harvest pest. Development of cultivars resistant to C. maculatus population growth in storage could increase grain yield and quality and reduce reliance on insecticides. Here, we use a MAGIC (multi-parent, advanced-generation intercross) population of cowpea consisting of 305 recombinant inbred lines (RILs) to identify genetic variants associated with resistance to seed beetles. Because inferences regarding the genetic basis of resistance may depend on the source of the pest or the assay protocol, we used two divergent geographic populations of C. maculatus and two complementary assays to measure several aspects of resistance. Using polygenic genome-wide association mapping models, we found that the cowpea RILs harbor substantial additive-genetic variation for most resistance measures. Variation in several components of resistance, including larval development time and survival, was largely explained by one or several linked loci on chromosome 5. A second region on chromosome 8 explained increased seed resistance via the induction of early-exiting larvae. Neither of these regions contained genes previously associated with resistance to insects that infest grain legumes. We found some evidence of gene-gene interactions affecting resistance, but epistasis did not contribute substantially to resistance variation in this mapping population. The combination of mostly high heritabilities and a relatively consistent and simple genetic architecture increases the feasibility of breeding for enhanced resistance to C. maculatus.

Genetic Approaches for Sports Performance: How Far Away Are We?

Humans vary in their ‘natural ability’ related to sports performance. One facet of natural ability reflects so-called intrinsic ability or the ability to do well with minimal training. A second facet of natural ability is how rapidly an individual adapts to training; this is termed trainability. A third facet is the upper limit achievable after years of prolonged intense training; this represents both intrinsic ability and also trainability. There are other features of natural ability to consider, for example body size, because some events, sports, or positions favor participants of different sizes. In this context, the physiological determinants of elite endurance performance, especially running and cycling, are well known and can be used as a template to discuss these general issues. The key determinants of endurance performance include maximal oxygen uptake \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(\dot{V}{\text{O}}_{2\hbox{max} } )$$\end{document}(V˙O2max), the lactate threshold, and running economy (efficiency in the case of cycling or other sports). In this article, I use these physiological determinants to explore what is known about the genetics of endurance performance. My main conclusion is that at this time there are very few, if any, obvious relationships between these key physiological determinants of performance and DNA sequence variation. Several potential reasons for this lack of relationship will be discussed.

Combining Experimental Evolution and Genomics to Understand How Seed Beetles Adapt to a Marginal Host Plant

Genes that affect adaptive traits have been identified, but our knowledge of the genetic basis of adaptation in a more general sense (across multiple traits) remains limited. We combined population-genomic analyses of evolve-and-resequence experiments, genome-wide association mapping of performance traits, and analyses of gene expression to fill this knowledge gap and shed light on the genomics of adaptation to a marginal host (lentil) by the seed beetle Callosobruchus maculatus. Using population-genomic approaches, we detected modest parallelism in allele frequency change across replicate lines during adaptation to lentil. Mapping populations derived from each lentil-adapted line revealed a polygenic basis for two host-specific performance traits (weight and development time), which had low to modest heritabilities. We found less evidence of parallelism in genotype-phenotype associations across these lines than in allele frequency changes during the experiments. Differential gene expression caused by differences in recent evolutionary history exceeded that caused by immediate rearing host. Together, the three genomic datasets suggest that genes affecting traits other than weight and development time are likely to be the main causes of parallel evolution and that detoxification genes (especially cytochrome P450s and beta-glucosidase) could be especially important for colonization of lentil by C. maculatus.

Inconsistent reproductive isolation revealed by interactions between Catostomus fish species

Interactions between species are central to evolution and ecology, but we do not know enough about how outcomes of interactions between species vary across geographic locations, in heterogeneous environments, or over time. Ecological dimensions of interactions between species are known to vary, but evolutionary interactions such as the establishment and maintenance of reproductive isolation are often assumed to be consistent across instances of an interaction between species. Hybridization among Catostomus fish species occurs over a large and heterogeneous geographic area and across taxa with distinct evolutionary histories, which allows us to assess consistency in species interactions. We analyzed hybridization among six Catostomus species across the Upper Colorado River basin (US mountain west) and found extreme variation in hybridization across locations. Different hybrid crosses were present in different locations, despite similar species assemblages. Within hybrid crosses, hybridization varied from only first generation hybrids to extensive hybridization with backcrossing. Variation in hybridization outcomes might result from uneven fitness of hybrids across locations, polymorphism in genetic incompatibilities, chance, unidentified historical contingencies, or some combination thereof. Our results suggest caution in assuming that one or a few instances of hybridization represent all interactions between the focal species, as species interactions vary substantially across locations.

Biology of VO2 max: looking under the physiology lamp

In this review, we argue that several key features of maximal oxygen uptake (VO₂ max) should underpin discussions about the biological and reductionist determinants of its interindividual variability: (i) training-induced increases in VO₂ max are largely facilitated by expansion of red blood cell volume and an associated improvement in stroke volume, which also adapts independent of changes in red blood cell volume. These general concepts are also informed by cross-sectional studies in athletes that have very high values for VO₂ max. Therefore, (ii) variations in VO₂ max improvements with exercise training are also likely related to variations in these physiological determinants. (iii) All previously untrained individuals will respond to endurance exercise training in terms of improvements in VO₂ max provided the stimulus exceeds a certain volume and/or intensity. Thus, genetic analysis and/or reductionist studies performed to understand or predict such variations might focus specifically on DNA variants or other molecular phenomena of relevance to these physiological pathways.

Absence of population structure across elevational gradients despite large phenotypic variation in mountain chickadees (Poecile gambeli)

Montane habitats are characterized by predictably rapid heterogeneity along elevational gradients and are useful for investigating the consequences of environmental heterogeneity for local adaptation and population genetic structure. Food-caching mountain chickadees inhabit a continuous elevation gradient in the Sierra Nevada, and birds living at harsher, high elevations have better spatial memory ability and exhibit differences in male song structure and female mate preference compared to birds inhabiting milder, low elevations. While high elevation birds breed, on average, two weeks later than low elevation birds, the extent of gene flow between elevations is unknown. Despite phenotypic variation and indirect evidence for local adaptation, population genetic analyses based on 18 073 single nucleotide polymorphisms across three transects of high and low elevation populations provided no evidence for genetic differentiation. Analyses based on individual genotypes revealed no patterns of clustering, pairwise estimates of genetic differentiation (F_ST, Nei's D) were very low, and AMOVA revealed no evidence for genetic variation structured by transect or by low and high elevation sites within transects. In addition, we found no consistent evidence for strong parallel allele frequency divergence between low and high elevation sites within the three transects. Large elevation-related phenotypic variation may be maintained by strong selection despite gene flow and future work should focus on the mechanisms underlying such variation.

What, if anything, are hybrids: enduring truths and challenges associated with population structure and gene flow

Hybridization is a potent evolutionary process that can affect the origin, maintenance, and loss of biodiversity. Because of its ecological and evolutionary consequences, an understanding of hybridization is important for basic and applied sciences, including conservation biology and agriculture. Herein, we review and discuss ideas that are relevant to the recognition of hybrids and hybridization. We supplement this discussion with simulations. The ideas we present have a long history, particularly in botany, and clarifying them should have practical consequences for managing hybridization and gene flow in plants. One of our primary goals is to illustrate what we can and cannot infer about hybrids and hybridization from molecular data; in other words, we ask when genetic analyses commonly used to study hybridization might mislead us about the history or nature of gene flow and selection. We focus on patterns of variation when hybridization is recent and populations are polymorphic, which are particularly informative for applied issues, such as contemporary hybridization following recent ecological change. We show that hybridization is not a singular process, but instead a collection of related processes with variable outcomes and consequences. Thus, it will often be inappropriate to generalize about the threats or benefits of hybridization from individual studies, and at minimum, it will be important to avoid categorical thinking about what hybridization and hybrids are. We recommend potential sampling and analytical approaches that should help us confront these complexities of hybridization.

G72 primate-specific gene: a still enigmatic element in psychiatric disorders

Numerous studies have demonstrated a link between genetic markers on chromosome 13 and schizophrenia, bipolar affective disorder, and other psychiatric phenotypes. The G72/G30 genes (transcribed in opposite directions) are located on chromosome 13q33, a region demonstrating strong evidence for linkage with various neuropsychiatric disorders. G72/G30 was identified in 2002 as a schizophrenia susceptibility locus; however, subsequent association studies did not reach consensus on single SNPs within the locus. Simultaneously, a new vision for the genetic architecture of psychiatric disorders suggested that schizophrenia was a quantitative trait, therefore ascribable to potentially hundreds of genes and subjected to the vagaries of the environment. The main protein product of G72 gene is named pLG72 or D-amino acid oxidase activator DAOA (153 amino acids) and its function is still debated. Functional analyses, also showing controversial results, indicate that pLG72 contributes to N-methyl-D-aspartate receptor modulation by affecting activity of the flavoprotein D-amino acid oxidase, the enzyme responsible for degrading the neuromodulator D-serine. In this review we, for the first time, summarize findings from molecular genetic linkage and association studies concerning G72 gene, cellular and molecular studies on pLG72, and investigations performed on G72/G30 transgenic mice. This will help elucidate the role of psychosis susceptibility genes, which will have a major impact on our understanding of disease pathophysiology and thus change classification and treatment.

A combined coalescence gene-dropping tool for evaluating genomic selection in complex scenarios (ms2gs)

We present ms2gs, a combined coalescence - gene dropping (i.e. backward-forward) simulator for complex traits. It therefore aims at combining the advantages of both approaches. It is primarily conceived for very short term, recent scenarios such as those that are of interest in animal and plant breeding. It is very flexible in terms of defining QTL architecture and SNP ascertainment bias, and it allows for easy modelling of alternative markers such as RADs. It can use real sequence or chip data or generate molecular polymorphisms via the coalescence. It can generate QTL conditional on extant molecular information, such as low-density genotyping. It models (simplistically) sequence, imputation or genotyping errors. It requires as input both genotypic data in plink or ms formats, and a pedigree that is used to perform the gene dropping. By default, it compares accuracy for BLUP, SNP ascertained data, sequence, and causal SNPs. It employs VanRaden's linear (GBLUP) and nonlinear method for incorporating molecular information. To illustrate the program, we present a small application in a half-sib population and a multiparental (MAGIC) cross. The program, manual and examples are available at https://github.com/mperezenciso/ms2gs.

Chemical communication of queen supergene status in an ant

Traits of interest to evolutionary biologists often have complex genetic architectures, the nature of which can confound traditional experimental study at single levels of analysis. In the fire ant Solenopsis invicta, the presence of a Mendelian 'supergene' is both necessary and sufficient to induce a shift in a fundamental property of social organization, from single-queen (monogyne) to multiple-queen (polygyne) colonies. This selfish genetic element, termed the Social b (Sb) supergene, contains > 600 genes that collectively promote its fitness by inducing the characteristic polygyne syndrome, in part by causing polygyne workers to accept only queens bearing the Sb element (a behaviour termed 'worker Sb discrimination'). Here, we employ a newly developed behavioural assay to reveal that polygyne workers, many of which bear the Sb element, employ chemical cues on the cuticle of queens to achieve worker Sb discrimination, but we found no evidence for such pheromonally mediated worker Sb discrimination in monogyne workers, which universally lack the Sb element. This polygyne worker Sb discrimination was then verified through a 'green beard' effect previously described in this system. We thus have demonstrated that the Sb element is required both for production of relevant chemical cues of queens and for expression of the behaviours of workers that collectively result in worker Sb discrimination. This information fills a critical gap in the map between genotype and complex phenotype in S. invicta by restricting the search for candidate genes and molecules involved in producing this complex social trait to factors associated with the Sb element itself.

Sequence- vs. chip-assisted genomic selection: accurate biological information is advised

Background

The development of next-generation sequencing technologies (NGS) has made the use of whole-genome sequence data for routine genetic evaluations possible, which has triggered a considerable interest in animal and plant breeding fields. Here, we investigated whether complete or partial sequence data can improve upon existing SNP (single nucleotide polymorphism) array-based selection strategies by simulation using a mixed coalescence - gene-dropping approach.

Results

We simulated 20 or 100 causal mutations (quantitative trait nucleotides, QTN) within 65 predefined ‘gene’ regions, each 10 kb long, within a genome composed of ten 3-Mb chromosomes. We compared prediction accuracy by cross-validation using a medium-density chip (7.5 k SNPs), a high-density (HD, 17 k) and sequence data (335 k). Genetic evaluation was based on a GBLUP method. The simulations showed: (1) a law of diminishing returns with increasing number of SNPs; (2) a modest effect of SNP ascertainment bias in arrays; (3) a small advantage of using whole-genome sequence data vs. HD arrays i.e. ~4%; (4) a minor effect of NGS errors except when imputation error rates are high (≥20%); and (5) if QTN were known, prediction accuracy approached 1. Since this is obviously unrealistic, we explored milder assumptions. We showed that, if all SNPs within causal genes were included in the prediction model, accuracy could also dramatically increase by ~40%. However, this criterion was highly sensitive to either misspecification (including wrong genes) or to the use of an incomplete gene list; in these cases, accuracy fell rapidly towards that reached when all SNPs from sequence data were blindly included in the model.

Conclusions

Our study shows that, unless an accurate prior estimate on the functionality of SNPs can be included in the predictor, there is a law of diminishing returns with increasing SNP density. As a result, use of whole-genome sequence data may not result in a highly increased selection response over high-density genotyping.

Evolutionary genetics as a tool to target genes involved in phenotypes of medical relevance

There is an increasing interest in detecting genes, or genomic regions, that have been targeted by natural selection. Indeed, the evolutionary approach for inferring the action of natural selection in the human genome represents a powerful tool for predicting regions of the genome potentially associated with disease and of interest in epidemiological genetic studies. Here, we review several examples going from candidate gene studies associated with specific phenotypes, including nutrition, infectious disease and climate adaptation, to whole genome scans for natural selection. All these studies illustrate the power of the evolutionary approach in identifying regions of the genome having played a major role in human survival and adaptation.

Unraveling genetic origin of aging-related traits: evolving concepts

Discovering the genetic origin of aging-related traits could greatly advance strategies aiming to extend health span. The results of genome-wide association studies (GWAS) addressing this problem are controversial, and new genetic concepts have been fostered to advance the progress in the field. A limitation of GWAS and new genetic concepts is that they do not thoroughly address specifics of aging-related traits. Integration of theoretical concepts in genetics and aging research with empirical evidence from different disciplines highlights the conceptual problems in studies of genetic origin of aging-related traits. To address these problems, novel approaches of systemic nature are required. These approaches should adopt the non-deterministic nature of linkage of genes with aging-related traits and, consequently, reinforce research strategies for improving our understanding of mechanisms shaping genetic effects on these traits. Investigation of mechanisms will help determine conditions that activate specific genetic variants or profiles and explore to what extent these conditions that shape genetic effects are conserved across human lives and generations.

Evolution at two levels of gene expression in yeast

Despite the greater functional importance of protein levels, our knowledge of gene expression evolution is based almost entirely on studies of mRNA levels. In contrast, our understanding of how translational regulation evolves has lagged far behind. Here we have applied ribosome profiling—which measures both global mRNA levels and their translation rates—to two species of Saccharomyces yeast and their interspecific hybrid in order to assess the relative contributions of changes in mRNA abundance and translation to regulatory evolution. We report that both cis- and trans-acting regulatory divergence in translation are abundant, affecting at least 35% of genes. The majority of translational divergence acts to buffer changes in mRNA abundance, suggesting a widespread role for stabilizing selection acting across regulatory levels. Nevertheless, we observe evidence of lineage-specific selection acting on several yeast functional modules, including instances of reinforcing selection acting at both levels of regulation. Finally, we also uncover multiple instances of stop-codon readthrough that are conserved between species. Our analysis reveals the underappreciated complexity of post-transcriptional regulatory divergence and indicates that partitioning the search for the locus of selection into the binary categories of “coding” versus “regulatory” may overlook a significant source of selection, acting at multiple regulatory levels along the path from genotype to phenotype.

The many faces of pleiotropy

Pleiotropy is the well-established phenomenon of a single gene affecting multiple traits. It has long played a central role in theoretical, experimental, and clinical research in genetics, development, molecular biology, evolution, and medicine. In recent years, genomic techniques have brought data to bear on fundamental questions about the nature and extent of pleiotropy. However, these efforts are plagued by conceptual difficulties derived from disparate meanings and interpretations of pleiotropy. Here, we describe distinct uses of the pleiotropy concept and explain the pitfalls associated with applying empirical data to them. We conclude that, for any question about the nature or extent of pleiotropy, the appropriate answer is always 'What do you mean?'.

Lost in the map

Organismal development and evolution are complex, multifaceted processes that depend intimately on context. They are subject to environmental influences, chance appearance and fixation of mutations, and numerous other idiosyncrasies. Genomics is detailing the molecular signature of effects of these mechanisms on phenotypes, but because numerous distinct evolutionary explanations can produce a given genomic pattern, the molecular details, rather than elucidating process, typically distract from explanatory insight and contribute little to predictive capability. While genomic research has burgeoned, direct study of evolutionary and developmental processes has lagged. We advocate for reinvigoration of direct study of process, along with refocusing of attention on questions of broad biological import, as more productive of urgently needed insights, which genomic approaches are not providing.

The genetic architecture of a complex ecological trait: host plant use in the specialist moth, Heliothis subflexa

We used genetic mapping to examine the genetic architecture of differences in host plant use between two species of noctuid moths, Heliothis subflexa, a specialist on Physalis spp., and its close relative, the broad generalist H. virescens. We introgressed H. subflexa chromosomes into the H. virescens background and analyzed 1462 backcross insects. The effects of H. subflexa-origin chromosomes were small when measured as the percent variation explained in backcross populations (0.2-5%), but were larger when considered in relation to the interspecific difference explained (1.5-165%). Most significant chromosomes had effects on more than one trait, and their effects varied between years, sexes, and genetic backgrounds. Different chromosomes could produce similar phenotypes, suggesting that the same trait might be controlled by different chromosomes in different backcross populations. It appears that many loci of small effect contribute to the use of Physalis by H. subflexa. We hypothesize that behavioral changes may have paved the way for physiological adaptation to Physalis by the generalist ancestor of H. subflexa and H. virescens.

Dissection of complex adult traits in a mouse synthetic population

Finding the causative genetic variations that underlie complex adult traits is a significant experimental challenge. The unbiased search strategy of genome-wide association (GWAS) has been used extensively in recent human population studies. These efforts, however, typically find only a minor fraction of the genetic loci that are predicted to affect variation. As an experimental model for the analysis of adult polygenic traits, we measured a mouse population for multiple phenotypes and conducted a genome-wide search for effector loci. Complex adult phenotypes, related to body size and bone structure, were measured as component phenotypes, and each subphenotype was associated with a genomic spectrum of candidate effector loci. The strategy successfully detected several loci for the phenotypes, at genome-wide significance, using a single, modest-sized population (N = 505). The effector loci each explain 2%–10% of the measured trait variation and, taken together, the loci can account for over 25% of a trait's total population variation. A replicate population (N = 378) was used to confirm initially observed loci for one trait (femur length), and, when the two groups were merged, the combined population demonstrated increased power to detect loci. In contrast to human population studies, our mouse genome-wide searches find loci that individually explain a larger fraction of the observed variation. Also, the additive effects of our detected mouse loci more closely match the predicted genetic component of variation. The genetic loci discovered are logical candidates for components of the genetic networks having evolutionary conservation with human biology.

Evolutionary molecular medicine

Evolution has long provided a foundation for population genetics, but some major advances in evolutionary biology from the twentieth century that provide foundations for evolutionary medicine are only now being applied in molecular medicine. They include the need for both proximate and evolutionary explanations, kin selection, evolutionary models for cooperation, competition between alleles, co-evolution, and new strategies for tracing phylogenies and identifying signals of selection. Recent advances in genomics are transforming evolutionary biology in ways that create even more opportunities for progress at its interfaces with genetics, medicine, and public health. This article reviews 15 evolutionary principles and their applications in molecular medicine in hopes that readers will use them and related principles to speed the development of evolutionary molecular medicine.

The changing landscape of genetic testing and its impact on clinical and laboratory services and research in Europe

The arrival of new genetic technologies that allow efficient examination of the whole human genome (microarray, next-generation sequencing) will impact upon both laboratories (cytogenetic and molecular genetics in the first instance) and clinical/medical genetic services. The interpretation of analytical results in terms of their clinical relevance and the predicted health status poses a challenge to both laboratory and clinical geneticists, due to the wealth and complexity of the information obtained. There is a need to discuss how to best restructure the genetic services logistically and to determine the clinical utility of genetic testing so that patients can receive appropriate advice and genetic testing. To weigh up the questions and challenges of the new genetic technologies, the European Society of Human Genetics (ESHG) held a series of workshops on 10 June 2010 in Gothenburg. This was part of an ESHG satellite symposium on the 'Changing landscape of genetic testing', co-organized by the ESHG Genetic Services Quality and Public and Professional Policy Committees. The audience consisted of a mix of geneticists, ethicists, social scientists and lawyers. In this paper, we summarize the discussions during the workshops and present some of the identified ways forward to improve and adapt the genetic services so that patients receive accurate and relevant information. This paper covers ethics, clinical utility, primary care, genetic services and the blurring boundaries between healthcare and research.

Evolution of a membrane protein regulon in Saccharomyces

Expression variation is widespread between species. The ability to distinguish regulatory change driven by natural selection from the consequences of neutral drift remains a major challenge in comparative genomics. In this work, we used observations of mRNA expression and promoter sequence to analyze signatures of selection on groups of functionally related genes in Saccharomycete yeasts. In a survey of gene regulons with expression divergence between Saccharomyces cerevisiae and S. paradoxus, we found that most were subject to variation in trans-regulatory factors that provided no evidence against a neutral model. However, we identified one regulon of membrane protein genes controlled by unlinked cis- and trans-acting determinants with coherent effects on gene expression, consistent with a history of directional, nonneutral evolution. For this membrane protein group, S. paradoxus alleles at regulatory loci were associated with elevated expression and altered stress responsiveness relative to other yeasts. In a phylogenetic comparison of promoter sequences of the membrane protein genes between species, the S. paradoxus lineage was distinguished by a short branch length, indicative of strong selective constraint. Likewise, sequence variants within the S. paradoxus population, but not across strains of other yeasts, were skewed toward low frequencies in promoters of genes in the membrane protein regulon, again reflecting strong purifying selection. Our results support a model in which a distinct expression program for the membrane protein genes in S. paradoxus has been preferentially maintained by negative selection as the result of an increased importance to organismal fitness. These findings illustrate the power of integrating expression- and sequence-based tests of natural selection in the study of evolutionary forces that underlie regulatory change.

The QTN program and the alleles that matter for evolution: all that's gold does not glitter

The search for the alleles that matter, the quantitative trait nucleotides (QTNs) that underlie heritable variation within populations and divergence among them, is a popular pursuit. But what is the question to which QTNs are the answer? Although their pursuit is often invoked as a means of addressing the molecular basis of phenotypic evolution or of estimating the roles of evolutionary forces, the QTNs that are accessible to experimentalists, QTNs of relatively large effect, may be uninformative about these issues if large-effect variants are unrepresentative of the alleles that matter. Although 20th century evolutionary biology generally viewed large-effect variants as atypical, the field has recently undergone a quiet realignment toward a view of readily discoverable large-effect alleles as the primary molecular substrates for evolution. I argue that neither theory nor data justify this realignment. Models and experimental findings covering broad swaths of evolutionary phenomena suggest that evolution often acts via large numbers of small-effect polygenes, individually undetectable. Moreover, these small-effect variants are different in kind, at the molecular level, from the large-effect alleles accessible to experimentalists. Although discoverable QTNs address some fundamental evolutionary questions, they are essentially misleading about many others.

Is life law-like?

Genes are generally assumed to be primary biological causes of biological phenotypes and their evolution. In just over a century, a research agenda that has built on Mendel's experiments and on Darwin's theory of natural selection as a law of nature has had unprecedented scientific success in isolating and characterizing many aspects of genetic causation. We revel in these successes, and yet the story is not quite so simple. The complex cooperative nature of genetic architecture and its evolution include teasingly tractable components, but much remains elusive. The proliferation of data generated in our "omics" age raises the question of whether we even have (or need) a unified theory or "law" of life, or even clear standards of inference by which to answer the question. If not, this not only has implications for the widely promulgated belief that we will soon be able to predict phenotypes like disease risk from genes, but also speaks to the limitations in the underlying science itself. Much of life seems to be characterized by ad hoc, ephemeral, contextual probabilism without proper underlying distributions. To the extent that this is true, causal effects are not asymptotically predictable, and new ways of understanding life may be required.

Systems biology and heart failure: concepts, methods, and potential research applications

Dramatic advances in molecular biology dominated twentieth century biomedical science and delineated the function of individual genes and molecules in exquisite detail. However, biological processes cannot be fully understood based on the properties of individual genes and molecules alone, since these elements act in concert to enable the specific functions that make for living cells and organisms. The discipline of systems biology provides a novel conceptual framework for understanding biological phenomenon. Systems biology synthesizes information concerning the interactions of genes and molecules and allows characterization of the supramolecular networks and functional modules that represent the most essential aspects of cell organization and physiology.

mGluR7 genetics and alcohol: intersection yields clues for addiction

Development of addiction to alcohol or other substances can be attributed in part to exposure-dependent modifications at synaptic efficacy leading to an organism which functions at an altered homeostatic setpoint. Genetic factors may also influence setpoints and the stability of the homeostatic system of an organism. Quantitative genetic analysis of voluntary alcohol drinking, and mapping of the involved genes in the quasi-congenic Recombinant QTL Introgression strain system, identified Eac2 as a Quantitative Trait Locus (QTL) on mouse chromosome 6 which explained 18% of the variance with an effect size of 2.09 g/kg/day alcohol consumption, and Grm7 as a quantitative trait gene underlying Eac2 [Vadasz et al. in Neurochem Res 32:1099-1112, 100, Genomics 90:690-702, 102]. In earlier studies, the product of Grm7 mGluR7, a G protein-coupled receptor, has been implicated in stress systems [Mitsukawa et al. in Proc Natl Acad Sci USA 102:18712-18717, 63], anxiety-like behaviors [Cryan et al. in Eur J Neurosci 17:2409-2417, 14], memory [Holscher et al. in Learn Mem 12:450-455, 26], and psychiatric disorders (e.g., [Mick et al. in Am J Med Genet B Neuropsychiatr Genet 147B:1412-1418, 61; Ohtsuki et al. in Schizophr Res 101:9-16, 72; Pergadia et al. in Paper presented at the 38th Annual Meeting of the Behavior Genetics Association, Louisville, Kentucky, USA, 76]. Here, in experiments with mice, we show that (1) Grm7 knockout mice express increased alcohol consumption, (2) sub-congenic, and congenic mice carrying a Grm7 variant characterized by higher Grm7 mRNA drink less alcohol, and show a tendency for higher circadian dark phase motor activity in a wheel running paradigm, respectively, and (3) there are significant genetic differences in Grm7 mRNA abundance in the mouse brain between congenic and background mice identifying brain areas whose function is implicated in addiction related processes. We hypothesize that metabotropic glutamate receptors may function as regulators of homeostasis, and Grm7 (mGluR7) is involved in multiple processes (including stress, circadian activity, reward control, memory, etc.) which interact with substance use and the development of addiction. In conclusion, we suggest that mGluR7 is a significant new therapeutic target in addiction and related neurobehavioral disorders.

Evolutionary genomics of animal personality

Research on animal personality can be approached from both a phenotypic and a genetic perspective. While using a phenotypic approach one can measure present selection on personality traits and their combinations. However, this approach cannot reconstruct the historical trajectory that was taken by evolution. Therefore, it is essential for our understanding of the causes and consequences of personality diversity to link phenotypic variation in personality traits with polymorphisms in genomic regions that code for this trait variation. Identifying genes or genome regions that underlie personality traits will open exciting possibilities to study natural selection at the molecular level, gene-gene and gene-environment interactions, pleiotropic effects and how gene expression shapes personality phenotypes. In this paper, we will discuss how genome information revealed by already established approaches and some more recent techniques such as high-throughput sequencing of genomic regions in a large number of individuals can be used to infer micro-evolutionary processes, historical selection and finally the maintenance of personality trait variation. We will do this by reviewing recent advances in molecular genetics of animal personality, but will also use advanced human personality studies as case studies of how molecular information may be used in animal personality research in the near future.

Evolutionary principles and their practical application

Evolutionary principles are now routinely incorporated into medicine and agriculture. Examples include the design of treatments that slow the evolution of resistance by weeds, pests, and pathogens, and the design of breeding programs that maximize crop yield or quality. Evolutionary principles are also increasingly incorporated into conservation biology, natural resource management, and environmental science. Examples include the protection of small and isolated populations from inbreeding depression, the identification of key traits involved in adaptation to climate change, the design of harvesting regimes that minimize unwanted life-history evolution, and the setting of conservation priorities based on populations, species, or communities that harbor the greatest evolutionary diversity and potential. The adoption of evolutionary principles has proceeded somewhat independently in these different fields, even though the underlying fundamental concepts are the same. We explore these fundamental concepts under four main themes: variation, selection, connectivity, and eco-evolutionary dynamics. Within each theme, we present several key evolutionary principles and illustrate their use in addressing applied problems. We hope that the resulting primer of evolutionary concepts and their practical utility helps to advance a unified multidisciplinary field of applied evolutionary biology.

The emergence of human-evolutionary medical genomics

In this review, I describe how evolutionary genomics is uniquely suited to spearhead advances in understanding human disease risk, owing to the privileged position of genes as fundamental causes of phenotypic variation, and the ability of population genetic and phylogenetic methods to robustly infer processes of natural selection, drift, and mutation from genetic variation at the levels of family, population, species, and clade. I first provide an overview of models for the origins and maintenance of genetically based disease risk in humans. I then discuss how analyses of genetic disease risk can be dovetailed with studies of positive and balancing selection, to evaluate the degree to which the 'genes that make us human' also represent the genes that mediate risk of polygenic disease. Finally, I present four basic principles for the nascent field of human evolutionary medical genomics, each of which represents a process that is nonintuitive from a proximate perspective. Joint consideration of these principles compels novel forms of interdisciplinary analyses, most notably studies that (i) analyze tradeoffs at the level of molecular genetics, and (ii) identify genetic variants that are derived in the human lineage or in specific populations, and then compare individuals with derived versus ancestral alleles.

Population genetics of genomics-based crop improvement methods

Many genome-wide association studies (GWAS) in humans are concluding that, even with very large sample sizes and high marker densities, most of the genetic basis of complex traits may remain unexplained. At the same time, recent research in plant GWAS is showing much greater success with fewer resources. Both GWAS and genomic selection (GS), a method for predicting phenotypes by the use of genome-wide marker data, are receiving considerable attention among plant breeders. In this review we explore how differences in population genetic histories, as well as past selection for traits of interest, have produced trait architectures and patterns of linkage disequilibrium (LD) that frequently differ dramatically between domesticated plants and humans, making detection of quantitative trait loci (QTL) effects in crops more rewarding and less costly than in humans.

Refined QTLs of osteoporosis-related traits by linkage analysis with genome-wide SNPs: Framingham SHARe

Genome-wide association studies (GWAS) using high-density array of single-nucleotide polymorphisms (SNPs) offer an unbiased strategy to identify new candidate genes for osteoporosis. We used a subset of autosomal SNPs from the Affymetrix 500K+50K SNP GeneChip marker set to examine genetic linkage with multiple highly heritable osteoporosis-related traits, including BMD of the hip and spine, heel ultrasound (attenuation and speed of sound), and geometric indices of the hip, in two generations from the Framingham Osteoporosis Study. Variance component linkage analysis was performed using normalized residuals (adjusted for age, height, BMI, and estrogen status in women). Multipoint linkage analyses produced LOD scores > or =3.0 for BMD on chromosomes (chr.) 9 and 11 and for ultrasound speed of sound on chr. 5. Hip geometric traits were linked with higher LOD scores, such as with shaft width on chr. 4 (LOD=3.9) and chr. 16 (LOD=3.8) and with shaft section modulus on chr. 22 (LOD=4.0). LOD score > or =5.0 was obtained for femoral neck width on chr. 7. In conclusion, with an SNP-based linkage approach, we identified several novel potential QTLs and confirmed previously identified chromosomal regions linked to bone mass and geometry. Subsequent focus on the spectrum of genetic polymorphisms in these refined regions may contribute to finding variants predisposing to osteoporosis.

Polygenic and directional regulatory evolution across pathways in Saccharomyces

The search to understand how genomes innovate in response to selection dominates the field of evolutionary biology. Powerful molecular evolution approaches have been developed to test individual loci for signatures of selection. In many cases, however, an organism's response to changes in selective pressure may be mediated by multiple genes, whose products function together in a cellular process or pathway. Here we assess the prevalence of polygenic evolution in pathways in the yeasts Saccharomyces cerevisiae and S. bayanus. We first established short-read sequencing methods to detect cis-regulatory variation in a diploid hybrid between the species. We then tested for the scenario in which selective pressure in one species to increase or decrease the activity of a pathway has driven the accumulation of cis-regulatory variants that act in the same direction on gene expression. Application of this test revealed a variety of yeast pathways with evidence for directional regulatory evolution. In parallel, we also used population genomic sequencing data to compare protein and cis-regulatory variation within and between species. We identified pathways with evidence for divergence within S. cerevisiae, and we detected signatures of positive selection between S. cerevisiae and S. bayanus. Our results point to polygenic, pathway-level change as a common evolutionary mechanism among yeasts. We suggest that pathway analyses, including our test for directional regulatory evolution, will prove to be a relevant and powerful strategy in many evolutionary genomic applications.

Genetic and environmental influences on cannabis use initiation and problematic use: a meta-analysis of twin studies

BACKGROUND

Because cannabis use is associated with social, physical and psychological problems, it is important to know what causes some individuals to initiate cannabis use and a subset of those to become problematic users. Previous twin studies found evidence for both genetic and environmental influences on vulnerability, but due to considerable variation in the results it is difficult to draw clear conclusions regarding the relative magnitude of these influences.

METHODS

A systematic literature search identified 28 twin studies on cannabis use initiation and 24 studies on problematic cannabis use. The proportion of total variance accounted for by genes (A), shared environment (C) and unshared environment (E) in (i) initiation of cannabis use and (ii) problematic cannabis use was calculated by averaging corresponding A, C and E estimates across studies from independent cohorts and weighting by sample size.

RESULTS

For cannabis use initiation, A, C and E estimates were 48%, 25% and 27% in males and 40%, 39% and 21% in females. For problematic cannabis use A, C and E estimates were 51%, 20% and 29% for males and 59%, 15% and 26% for females. Confidence intervals of these estimates are considerably narrower than those in the source studies.

CONCLUSIONS

Our results indicate that vulnerability to both cannabis use initiation and problematic use was influenced significantly by A, C and E. There was a trend for a greater C and lesser A component for cannabis use initiation compared to problematic use for females.

Evolution in health and medicine Sackler colloquium: Making evolutionary biology a basic science for medicine

New applications of evolutionary biology in medicine are being discovered at an accelerating rate, but few physicians have sufficient educational background to use them fully. This article summarizes suggestions from several groups that have considered how evolutionary biology can be useful in medicine, what physicians should learn about it, and when and how they should learn it. Our general conclusion is that evolutionary biology is a crucial basic science for medicine. In addition to looking at established evolutionary methods and topics, such as population genetics and pathogen evolution, we highlight questions about why natural selection leaves bodies vulnerable to disease. Knowledge about evolution provides physicians with an integrative framework that links otherwise disparate bits of knowledge. It replaces the prevalent view of bodies as machines with a biological view of bodies shaped by evolutionary processes. Like other basic sciences, evolutionary biology needs to be taught both before and during medical school. Most introductory biology courses are insufficient to establish competency in evolutionary biology. Premedical students need evolution courses, possibly ones that emphasize medically relevant aspects. In medical school, evolutionary biology should be taught as one of the basic medical sciences. This will require a course that reviews basic principles and specific medical applications, followed by an integrated presentation of evolutionary aspects that apply to each disease and organ system. Evolutionary biology is not just another topic vying for inclusion in the curriculum; it is an essential foundation for a biological understanding of health and disease.

Evolution in health and medicine Sackler colloquium: Genetic architecture of a complex trait and its implications for fitness and genome-wide association studies

A model is investigated in which mutations that affect a complex trait (e.g., heart disease) also affect fitness because the trait is a component of fitness or because the mutations have pleiotropic effects on fitness. The model predicts that the genetic variance, and hence the heritability, in the trait is contributed by mutations at low frequency in the population, unless the mean strength of selection of mutations that affect the trait is very small or weakly selected mutations tend to contribute disproportionately to the trait compared with strongly selected mutations. Furthermore, it is shown that each rare mutation tends to contribute more to the variance than each common mutation. These results may explain why most genome-wide association studies have failed to find associations that explain much of the variance. It is also shown that most of the variance in fitness contributed by new nonsynonymous mutations is caused by mutations at very low frequency in the population. This implies that most low-frequency SNPs, which are observed in current resequencing studies of, for example, 100 chromosomes, probably have little impact on the variance in fitness or traits. Finally, it is shown that the variance contributed by a category of mutations (e.g., coding or regulatory) depends largely upon the mean strength of selection; this has implications for understanding which types of mutations are likely to be responsible for the variance in fitness and inherited disease.

Context-dependent associations between variation in risk of ischemic heart disease and variation in the 5' promoter region of the apolipoprotein E gene in Danish women

OBJECTIVE

Variations in the noncoding single-nucleotide polymorphisms (SNPs) at positions 560 and 832 in the 5' promoter region of the apolipoprotein E gene define genotypes that distinguish between high and low concentrations of plasma total and high-density lipoprotein cholesterol and triglycerides. We addressed whether these genotypes improve the prediction of ischemic heart disease (IHD) in subsamples of individuals defined by traditional risk factors and the genotypes defined by the epsilon(2), epsilon(3), and epsilon(4) alleles in exon 4 of the apolipoprotein E gene.

METHODS AND RESULTS

In a sample of 3686 female and 2772 male participants of the Copenhagen City Heart Study who were free of IHD events, 576 individuals (257 women, 7.0% and 319 men, 11.5%) were diagnosed as having developed IHD in 6.5 years of follow-up. Using a stepwise Patient Rule-Induction Method modeling strategy that acknowledges the complex pathobiology of IHD, we identified a subsample of 764 elderly women (> or =65 years) with hypertriglyceridemia who had a history of smoking, a history of hypertension, or a history of both in which the A(560)T(832)/A(560)T(832) and A(560)T(832)/A(560)G(832) 5' 2-SNP genotypes had a higher cumulative incidence of IHD (172/1000) compared to the incidence of 70/1000 in the total sample of women.

CONCLUSIONS

Our study validates that 5' apolipoprotein E genotypes improve the prediction of IHD and documents that the improvement is greatest in a subset defined by a particular combination of traditional risk factors in Copenhagen City Heart Study female participants. We discuss the use of these genotypes in medical risk assessment of IHD in the population represented by the Copenhagen City Heart Study.